Communications and Networking. 13th EAI International Conference, ChinaCom 2018, Chengdu, China, October 23-25, 2018, Proceedings

Research Article

User Scheduling for Large-Scale MIMO Downlink System Over Correlated Rician Fading Channels

Download
102 downloads
  • @INPROCEEDINGS{10.1007/978-3-030-06161-6_66,
        author={Tingting Sun and Xiao Li and Xiqi Gao},
        title={User Scheduling for Large-Scale MIMO Downlink System Over Correlated Rician Fading Channels},
        proceedings={Communications and Networking. 13th EAI International Conference, ChinaCom 2018, Chengdu, China, October 23-25, 2018, Proceedings},
        proceedings_a={CHINACOM},
        year={2019},
        month={1},
        keywords={User scheduling Rician fading Downlink},
        doi={10.1007/978-3-030-06161-6_66}
    }
    
  • Tingting Sun
    Xiao Li
    Xiqi Gao
    Year: 2019
    User Scheduling for Large-Scale MIMO Downlink System Over Correlated Rician Fading Channels
    CHINACOM
    Springer
    DOI: 10.1007/978-3-030-06161-6_66
Tingting Sun1,*, Xiao Li1, Xiqi Gao1
  • 1: Southeast University
*Contact email: stt19931124@seu.edu.cn

Abstract

In this paper, we investigate the downlink transmission, especially the user scheduling algorithm for single-cell multiple-input multiple-output (MIMO) system under correlated Rician fading channels. Under the assumption of only statistical channel state information (CSI) at the base station (BS), the statistical beamforming transmission is derived by maximizing the lower bound of the average signal-to-leakage-plus-noise ratio (). Based on this beamforming transmission algorithm, three user scheduling algorithms are proposed exploiting only statistical CSI: (1) maximum SLNR: schedule the user with the maximum SLNR; (2) most dissimilar: schedule the user that is most dissimilar to the already selected users; (3) modified-treating interference as noise (TIN): treat the inter-user interference as uncorrelated noise to each user’s useful signal and schedule the user with the largest signal-to-noise factor. Simulation results show that the proposed user scheduling algorithms perform well in achieving considerable sum rate.